Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved activity, selectivity, and safety.


The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by Reaxense.


Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.


We use our state-of-the-art dedicated workflow for designing focused libraries for protein-protein interfaces.


 

Fig. 1. The screening workflow of Receptor.AI

It features thorough molecular simulations of the target protein, both isolated and in complex with key partner proteins, complemented by ensemble virtual screening that accounts for conformational mobility in the unbound and complex states. The tentative binding sites are explored on the protein-protein interaction interface and at remote allosteric locations, encompassing the entire spectrum of potential mechanisms of action.


Our library distinguishes itself through several key aspects:


  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.

  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.

  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.

  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.


PARTNER
Receptor.AI
 
UPACC
P26842

UPID:
CD27_HUMAN

ALTERNATIVE NAMES:
CD27L receptor; T-cell activation antigen CD27; T14; Tumor necrosis factor receptor superfamily member 7

ALTERNATIVE UPACC:
P26842; B2RDZ0

BACKGROUND:
The CD27 antigen, integral to T-cell survival and function, is recognized by its various names including CD27L receptor and Tumor necrosis factor receptor superfamily member 7. Its roles encompass receptor activity for CD70/CD27L and potential involvement in apoptosis via SIVA1 association.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of CD27 antigen could open doors to potential therapeutic strategies for Lymphoproliferative syndrome 2, highlighting the importance of this protein in immune regulation and its potential as a target in immunodeficiency disorders.

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